Getting Code Near the Data: A Study of Generating Customized Data Intensive Scientific Workflows with Domain Specific Language

Document Type

Conference Proceeding

Abstract

The amount of data produced in modern biological experiments such as Nuclear Magnetic Resonance (NMR) analysis far exceeds the processing capability of a single machine. The present state-of-the-art is taking the ”data to code”, the philosophy followed by many of the current service oriented workflow systems. However this is not feasible in some cases such as NMR data analysis, primarily due to the large scale of data.

The objective of this research is to bring ”code to data”, preferred in the cases when the data is extremely large. We present a DSL based approach to develop customized data intensive scientific workflows capable of running on Hadoop clusters. Our DSL has features to facilitate autogeneration of a Web service front end. These services can be used along with existing service oriented workflow systems. Biologists can use our approach either to implement complete workflows or expose mini workflows as services, all without any knowledge of the underlying complications of the Cloud environment.

APA Citation

Manjunatha, A., Ranabahu, A. H., Anderson, P. E., & Sheth, A. P. (2010). Getting Code Near the Data: A Study of Generating Customized Data Intensive Scientific Workflows with Domain Specific Language.
https://corescholar.libraries.wright.edu/knoesis/700

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